The emergence of the Internet has caused a shift in the methods of commercial activity towards automated purchasing, marketing, sales and distribution of products, services and bundles. The automated aspects of electronic commerce allow a one-to-one relationship between seller and buyer as compared with the traditional mass production and sales approach. However, most electronic commerce sales systems resemble simple catalog sales or intermediated exchange: Neither of these main approaches satisfies the ideal of automated commerce.
What is needed is a purchasing, sales, marketing and production system that emulates the way customers actually buy and manufacturers produce goods and services. By mirroring the economic psychology of buyers, a system can be developed that (1) is demand-based, (2) sets up a seller-side competition for buyers, (3) uses multivariate negotiation processes, (4) uses interactivity, (5) is information rich, (6) exploits systemic adaptivity that learns from data analysis and synthesis, (7) facilitates buyer aggregation and (8) employs customization. Applicant is the inventor of a system (Solomon, PCT WO 01/33464 A1), which performs these functions primarily in a centralized way (i.e., using intermediation processes, such as exchange or auction), but no system does so in a disintermediated way. The challenge of automated commercial operations is to develop such a disintermediated electronic commerce system. The present invention addresses these problems in novel and non-obvious ways.
The present invention derives from the convergence of several technologies involving distributed computing systems and multi-agent systems.
The evolution of the Internet, particularly the World Wide Web (Web), emerged as a distributed computing medium in which independent computers can access information by using browser or e-mail communications software. But the main uses of the Internet in e-commerce have focused on intermediated transactions. For consumers, most transactions resemble an electronic catalogue sales system, while for businesses most electronic transactions occur at a centralized portal or exchange.
However, a new generation of distributed database architectures is emerging with promising commercial applications. One prominent example of a new decentralized database structure that is organized for disintermediated information exchange is the GRID. Originally patterned after the electric power grid, which can move electricity from point to point, the GRID is intended to use distributed database architectures for large bandwidth applications such as supercomputer data flows.
These new distributed database architectures allow new data search and analytical methods. Traditionally, search engines have accessed large central databases that accumulate and structure the collection of data over a period of time. These technologies are limited to relational database structures, and restricted in analytical complexity. The new search technologies overcome these problems by exploiting distributed computing architectures and object-relational data structures.
Traditional data mining techniques have employed pattern recognition and statistical modeling algorithms in order to organize and assess large pools of data. One outcome of the use of data mining has been in the area of collaborative filtering where recommendations are made to customers on the basis of inferences of other customers' similar interests. But a new generation of artificial intelligence technologies provides the ability to produce complex data analyses and syntheses that reveal more accurate predictions because they adapt to changing circumstances. By integrating data analysis and synthesis tools with search and transaction tools, these recommendation and predictive capabilities are more useful.
Businesses have for decades tried to automate their internal computer and communications systems in order to improve efficiency and promote competitive advantages. One of the first attempts at business automation involved the use of “electronic data interchange” (EDI). EDI was a precursor to electronic commerce because it set up a system for businesses to communicate electronically in order to complete and track financial transactions. Most of the transactions used by EDI systems are financial, dealing primarily with payment processing. EDI simply automates paper processing of payment notices, remittances and receipt records, directly between companies.
A technology that is emerging to succeed EDI involves a new programming language—XML—and business registry—UDDI. These new technologies allow a more robust communication between businesses because products, services and bundles are indexed and catalogued for direct access. Though more robust than EDI, XML/UDDI systems are merely passive information-based formats that link businesses, similar to the yellow-pages.
Technologies to connect machines and people have been advanced by the advent of graphic user interface (GUI) technology applied to PCs through advanced operating systems. In addition to simpler GUIs, translation software has been used to bridge the gaps between different software applications. The development of a new generation of inter-agents that interface with human users and computer programs is a key evolution towards simpler, yet more powerful commercial transactions.
Multi-Agent Systems (MASs) are not new in academic circles. The attempt to develop MASs in distributed computing environments has been active for over a decade. With the increased automation of business computing systems, MASs have reshaped the factory floor, securities trading systems and complex communications networks. With the advent of AI technologies, most prominently GP, GA, NN and FL, MASs have emerged as a reborn technology category for computer scientists.
One of the most practical uses for MASs applies to negotiation systems. The development of the “contract net” (k-net) system for distributed problem solving acts as the pioneer idea for mediating distributed computer encounters, particularly for efficiently dividing limited computation resources in a network. Building on the k-net platform, prominent based market models for transaction negotiation include the Fishmarket, the Michigan AuctionBot, Tete-a-tete and SWARM. These systems attempt in different ways to model contracting processes so as to facilitate commercial transactions.
In addition to these transaction models, a subset of the computer science academic literature describes coordination of agents in a MAS. Organizing cooperating intelligent agents is a key challenge of computer science, because it involves calibrating rules that provide neutrality to the coordination (typically of buyers) in complex self-organizing systems.
Though there are automated systems that emulate manual transaction processes, most approaches merely represent evolutionary progress in the field. E-commerce approaches seek to integrate post-sale systems with payment processing and CRM systems. This is necessary to complete and track transactions and to develop and enhance personalized customer relationships in a single centralized system. Even more advanced automated systems can more fully integrate complex marketing and financial processes into the transaction system. Further, the transaction system can be part of a unified system that includes data analysis and synthesis and negotiation processes.